Abstract
Simulation of highway driving was traditionally the domain of virtual physics based models. Yet, traffic simulation is incomplete without considering the drivers’ conscious strategic and tactical behavior. These aspects can be naturally simulated through an agent-based driver model. In this paper, we describe a model of the strategic lane preferences of the drivers, with a special attention to the optimal lane positioning for a safe exit. Our experiments show that the simulated traffic of Orlando’s Highway 408 matches well with the real world traffic data. The increased simulation detail can be applied to crash prediction and the control of intelligent transportation system devices, such as variable speed limits.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Luo, Y., Bölöni, L.:Towards a more accurate agent-based multi-lane highway simulation. In: Proceedings of International Workshop on Agents in Traffic and Transportation (ATT10), in conjunction with the 9th Joint Conference on Autonomous and Multi-Agent Systems (AAMAS 2010), pp. 13–20. May 2010
Kesting, A., Treiber, M., Helbing, D.: General lane-changing model MOBIL for car-following models. Transp. Res. Rec. J. Transp. Res. Board. 1999(?1), 86–94 (2007)
Pande, A., Abdel-Aty, M.: Assessment of freeway traffic parameters leading to lane-change related collisions. Elsevier J. Accid. Anal. Prev. 38, 936–948 (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag London Limited
About this paper
Cite this paper
Luo, Y., Bölöni, L. (2011). Modeling Lane Preferences in Agent-Based Multi-Lane Highway Simulation. In: Gelenbe, E., Lent, R., Sakellari, G. (eds) Computer and Information Sciences II. Springer, London. https://doi.org/10.1007/978-1-4471-2155-8_47
Download citation
DOI: https://doi.org/10.1007/978-1-4471-2155-8_47
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-2154-1
Online ISBN: 978-1-4471-2155-8
eBook Packages: EngineeringEngineering (R0)